A dream is a succession of images, ideas, emotions, and sensations that usually occurs involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not fully understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]

Machine learning, AI, Conv Nets, Deep Learning, and Neural Nets … all rapidly maturing Artificial Intelligence technologies that have simultaneously become household jargon in the Valley. Tesla's self driving car, Amazon Alexa, Google Search, Facebook tag recommendations, Microsoft Cortana, and Apple Siri … all novel products leveraging the above mentioned AI technologies, developed by large tech mainstays, and increasingly popular nation wide. Technocrati cocktail banter is developed and largely kept in-house by large technology incumbents to develop new products and disrupt adjacent industries. That said, historically a rapid rise and maturation of a new technology germinates within the the confines of a select few labs, institutions, social classes, and corporations before hitting a critical juncture when, via technological or economic means, it rapidly democratizes and is made available to everyone. Clarifai's growing product suite around developer centric AI tools are leading exactly that charge: democratizing the Artificial Intelligence revolution.

UPDATE: Mar 20, 2016 - Added my new follow-up course on Deep Learning, which covers ways to speed up and improve vanilla backpropagation: momentum and Nesterov momentum, adaptive learning rate algorithms like AdaGrad and RMSProp, utilizing the GPU on AWS EC2, and stochastic batch gradient descent. We look at TensorFlow and Theano starting from the basics - variables, functions, expressions, and simple optimizations - from there, building a neural network seems simple! Deep learning is all the rage these days. What exactly is deep learning? Well, it all boils down to neural networks.

On-board processing will give every digital eye a very powerful brain. San Mateo-based Movidius may still be in the process of getting bought up by Intel, but the company's latest deal will put its low-power AI and computer vision platform into more than just DJI drones and Google VR headsets. The company announced today that the Movidius Myriad 2 Video Processing Unit (VPU) will soon power a new generation of Hikvision smart surveillance cameras capable of recognizing everything from suspicious packages to distracted drivers. While most deep-learning neural networks require a lot of cloud-based processing power, the same platform found in Movidius' Fathom AI-on-a-stick will allow Hikvision cameras to do more on-board processing. Hikvision's cameras have already been able to achieve around 99 percent accuracy in scenarios like identifying car models, detecting intruders, spotting suspicious baggage and even calling out drivers who don't buckle up.

Next month, Dr. Iris Pear will present her groundbreaking new study at the International Conference on Atomic and Nuclear Physics. Iris Pear – a play on "Siri Apple" – is the invention of Christophe Bartneck, an associate professor of computer science at New Zealand's University of Canterbury. The study in question is completely nonsensical, procedurally generated by iOS's autocomplete function. Why, then, did a conference for "leading academic scientists" select it for presentation? On Thursday, Dr. Bartneck received an invitation to submit research for an upcoming conference on nuclear physics.

The following is a list of, mostly free, machine learning online courses for beginners. First, and arguably the most popular course on this list, Machine Learning provides a broad introduction to machine learning, data mining, and statistical pattern recognition. The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas. The course is 11 weeks long and averages a 4.9/5 user rating, currently. It is free to take, but you can pay $79 for a certificate upon course completion.

Spookily powerful artificial intelligence (AI) systems may work so well because their structure exploits the fundamental laws of the universe, new research suggests. The new findings may help answer a longstanding mystery about a class of artificial intelligence that employ a strategy called deep learning. These deep learning or deep neural network programs, as they're called, are algorithms that have many layers in which lower-level calculations feed into higher ones. Deep neural networks often perform astonishingly well at solving problems as complex as beating the world's best player of the strategy board game Go or classifying cat photos, yet know one fully understood why. It turns out, one reason may be that they are tapping into the very special properties of the physical world, said Max Tegmark, a physicist at the Massachusetts Institute of Technology (MIT) and a co-author of the new research.

Unlike most other lists of top experts, this one is a hand-picked selection, not based on influence or Klout scores, or the number of Twitter followers and re-tweets, or other similar metrics. Each of these experts has his/her own Wikipedia page. Some might not even have a Twitter account. All of them have had a very strong academic and research career in the most prestigious places. Jeffrey Hawkins is the American founder of Palm Computing (where he invented the Palm Pilot) and Handspring (where he invented the Treo).

Darknet is one of the most interesting and thought provoking sci fi books that I have read in awhile. As someone who is deeply immersed in the fields of machine learning and artificial intelligence, I have come across or thought about many of the ideas that have been presented in this book, especially the central theme – autonomous agents that aided by our increasingly digital online worlds, become capable enough to run their own corporate entities. Technology is not quite there yet for a creation of such an agent, but it's probably much closer than most people realize. That's why it was really interesting to go through the intellectual exercise of imagining what kind of things would such an entity engage in if it comes to be. For that reason alone Darknet is very worthwhile read for all AI geeks out there.

People pass by a T-Mobile store in the Brooklyn borough of New York June 4, 2015. NEW YORK T-Mobile US Inc is the likeliest acquisition target as media companies seek a wireless partner following AT&T Inc's proposed 85.4 billion takeover of Time Warner Inc, analysts said. AT&T announced the deal late on Saturday, stoking urgency in the telecoms and media sectors, where carriers facing a saturated wireless market are looking for content to attract mobile users and producers of shows and movies are seeking digital distribution. T-Mobile took most of the wireless industry's subscriber and revenue growth in the third quarter. Its strong balance sheet and fast-growing wireless business makes it an attractive target for a pay-TV or media company, analysts said.